Different In Situ Immune Patterns between Primary Tumor and Lymph Node in Non-Small-Cell Lung Cancer: Potential Impact on Neoadjuvant Immunotherapy

Background Neoadjuvant immunotherapy is promising for locally advanced non-small-cell lung cancer (NSCLC). The in situ immune patterns, as a predictor of PD-1/PD-L1 blockade outcomes, of the primary tumor (PT) and metastatic lymph nodes (mLNs) are unknown. Methods Multiplex immunofluorescence staining and multispectral imaging were used to evaluate the in situ immune patterns of T cells (CD3+) and cytotoxic T cells (CD8+) in terms of density, location (center of tumor (CT) and invasive margin (IM)), and the PD-L1 expression status of tumor cells and stromal T cells of paired PTs and mLNs in 38 stage III NSCLCs. Results The densities of T cells and cytotoxic T cells were correlated between PTs and mLNs at both CT and IM. Higher densities of stromal T cells (S-CD3+) at CT and both S-CD3+ and cytotoxic T cells (S-CD8+) at IM were observed in mLNs compared to PTs, while in tumor compartment, there were no differences in the densities of T cells (T-CD3+) or cytotoxic T cells (T-CD8+). Only the density of stromal PD-L1-positive T cells (S-PD-L1+CD3+) at CT was correlated between PTs and mLNs, while the densities and frequencies of S-PD-L1+CD3+ at CT and IM of mLNs were higher than PTs. Combining positive score discordance of PD-L1 between PTs and mLNs was greater than tumor proportion score. Conclusions. In situ immune patterns of T cells and cytotoxic T cells were different between PTs and mLNs in NSCLC. The heterogeneity of the in situ immune patterns may result in different immune-mediated responses to neoadjuvant immunotherapy in PT and mLNs.


Introduction
Lung cancer is the leading cause of cancer-related death worldwide [1]. The discovery of programmed cell death 1 (PD-1) and its ligand (PD-L1) improved the management of advanced-stage lung cancer by PD-1/PD-L1 blockade [2][3][4]. To date, the most widely used biomarker for immunotherapy is PD-L1 expression on tumor or immune cells, although its accuracy for predicting the response to immunotherapy is insufficient [5,6]. The tumor immune microenvironment (TIME), particularly the in situ immune pattern or contexture, defined as the type, functional orientation, density, and location of adaptive immune cells within distinct tumor regions, demonstrates the effectiveness of host immune response to tumor or tumor-host interaction and may influence the efficacy of immunotherapy [7][8][9]. Moreover, this phenomenon exists not only in primary tumors (PTs) but also in metastatic lesions. For example, patients with liver metastases of colorectal cancer (CRC) with a higher density of tumor-infiltrating lymphocytes (TILs) at the invasive margin (IM) have prolonged progression-free survival with chemotherapy [10].
Compared to the TNM staging system, a scoring system based on the immune contexture and incorporating the host immune response, called immunoscore (IS) [11], is a useful prognostic factor for solid tumors, including non-small-cell lung cancer (NSCLC) [12][13][14][15]. Therefore, an international task force was established to incorporate the IS into the traditional classification, designated TNM-immune, to improve the prediction of the outcomes of malignancies [16,17]. According to the IS task force, CD3 and CD8 in two regions (center of tumor (CT) and IM), are used for validating the IS [16]. As the immune response to cancer depends on T cells that recognize cancer-associated antigens [18], CD3, as a pan-T cell marker, has a positive prognostic impact in NSCLC patients. In addition, patients with a high density of CD3+ TILs have a favorable prognosis [19,20]. CD8, a marker of cytotoxic T cells, which play a pivotal role in antitumor immune responses, is also a prognostic factor for NSCLC [17]. Recently, stromal CD8+ TILs at IM region were proved to be an independent prognostic factor and IS indicator for NSCLC [21].
Given that the in situ immune patterns of either PTs and metastases had prognostic and therapeutic implications, we used multiplex immunofluorescence and multispectral imaging to evaluate the in situ immune patterns of T cells (CD3+) and cytotoxic T cells (CD8+) in terms of their densities and locations to explore if there was a difference of in situ immune patterns between the PTs and the mLNs of NSCLC in this study. A preprint has previously been published [22], and analysis of PD-L1 expression on tumor cells and stromal T cells was conducted as well.

Patients and Specimens.
During the initial screening phase, treatment-naive patients who underwent lobectomy/ pneumonectomy with lymphadenectomy with curative intent from 2012 to 2016 were screened and retrieved from the electronic medical record database. Then, patients who were pathologically diagnosed with lung adenocarcinoma (ADC) or squamous cell carcinoma (SCC) with mediastinal lymph node metastases (N2) were identified using the electronic pathology database. Patients with EGFR mutation and EML4-ALK translocation were excluded in the meantime. We reviewed the pathological report in detail to identify the metastatic lymph node with the largest diameter in N2 stations. Finally, the paraffin sections of both the PTs and the mLNs were reviewed by two pathologists. Only samples with CT and IM at both PTs and mLNs were selected and sent for final analyses. Demographic data, smoking status, surgical procedure, and pathologic information were retrieved from medical records. Immune-related pathologic response criteria proposed by Cottrell et al. were used to evaluate PTs and mLNs following immunotherapy [23]. In their system, the total tumor bed is defined by residual viable tumor+necrosis+regression bed. The total tumor bed is estimated to calculate the percentage of immune-related residual viable tumor ðviable tumor area/total tumor bed area * 100Þ. This study was conducted in accordance with the amended Declaration of Helsinki. The institutional review board approved the study protocol, and written consent for tissue analyses was obtained from all patients preoperatively.
For multispectral imaging, stained slides were scanned and imaged using the Polaris System (PerkinElmer, Waltham, MA) to capture the fluorescent spectrum at 20 nm wavelength intervals from 420 to 720 nm, which were combined to build a single stack image. To extract the autofluorescence spectrum of tissue and each fluorescein, unstained and single-stained images were used. For multispectral unmixing, a spectral library was established using the extracted images and Inform 2.4 image analysis software (PerkinElmer, Waltham, MA). Using the spectral library, we generated reconstructed images of sections without autofluorescence. The multispectral images containing PD-L1, CD3, CD8A, and cytokeratin were analyzed by Inform 2.4 image-analysis software using the tissue finder tool to segment the images into the tumor compartment (presence of cytokeratin (CK) positivity), stroma compartment (absence of cytokeratin positivity), and blank tissue compartment (absence of cells). Individual cells (DAPI+) were identified by adaptive segmentation algorithms to identify colocalization of cell populations and compartments, which were labeled as follows: tumor cells (CK+), cells expressing PD-L1 (PD-L1+), tumor cells expressing PD-L1 (PD-L1+CK+), T cells (CD3+), cytotoxic T cells (CD8+), T cells expressing PD-L1 (PD-L1+CD3+), and cytotoxic T cells expressing PD-L1 (PD-L1+CD8+). Analyses using Pano-Score 1.0 software (Panovue, Beijing, China) generated a cell-by-cell identification report of cell populations in the three compartments, including their density (number of cells/mm 2 ).

Assessing
In Situ Immune Pattern. PTs and matched mLN sections at low magnification (×10) were scanned to identify CT and IM using the Polaris System (PerkinElmer, Waltham, MA) (Figure 1(a)), as described [16,21]. The same numbers of fields of view (FOVs) at high resolution (×20) were taken in each region, if possible. The numbers of FOVs were based on the size of viable tumor tissue, if the tumor tissue was too small, representative FOV would be taken and categorized as CT (Figure 1(b)). For tumor tissue that scattered and could not be divided into CT and IM regions, the FOV of each tumor area was collected and categorized as IM. The same numbers of FOVs at high resolution (×20) were taken in each region, if possible ( Figure 1).

Journal of Immunology Research
To compare the immune contexture of T cells (CD3+) and cytotoxic T cells (CD8+), the densities (cells/mm 2 ) of each between PTs and mLNs were sorted in descending order and matched in the same patient.

Assessment of PD-L1 Expression.
Because PD-L1 expression on tumor-infiltrating T cells reflects an ongoing immune response and has an intrinsically favorable prognostic impact [7], and patients with higher density and frequency of stromal PD-L1-positive regulatory T cells had a better response to immunotherapy [25], we investigated whether the densities or frequencies of stomal tumorinfiltrating T cells in CT and IM regions were correlated between PTs and mLNs. The highest density and frequency of stromal PD-L1-positive T cells (S-PD-L1+CD3+) in each region were analyzed. The frequency was calculated as the number of PD-L1-positive T cells divided by the number of CD3+ cells in the stroma compartment multiplied by 100. Additionally, views of CT scans with a minimum of 100 tumor cells were eligible for analyses of PD-L1 expression in PTs and mLNs [26]. PD-L1 expression on tumor cells was evaluated using the tumor proportion score (TPS), which was the number of PD-L1-stained tumor cells (PD-L1+CK+) divided by the total number of viable tumor cells (CK+) multiplied by 100 in the tumor compartment. PD-L1-stained cells were evaluated by calculating the combined positive score (CPS) in the total compartment, which was the number of PD-L1-stained cells (PD-L1+) divided by the total number of viable tumor cells (CK+) multiplied by 100. The TPS is considered positive at ≥1%, and the CPS at >1.

Clinicopathological Characteristics.
Thirty-eight patients were enrolled, and their clinicopathologic characteristics are shown in Table 1. All patients were pathologically staged as III, and the median age was 55.50 (range 34-72) years.

Different In Situ Immune Pattern of T Cells and Cytotoxic T Cells between PTs and mLNs.
Given that no significant difference was found between SCC and ADC regarding in situ immune pattern in this study, analyses were conducted for the entire cohort. In the CT and IM tumor compartments, the densities of T-CD3+ and T-CD8+ cells were not significantly different but were significantly correlated between PTs and mLNs (P < 0:0001). Therefore, the in situ immune patterns of T-CD3+ and T-CD8+ were reproduced from PTs to mLNs during metastasis in both CT and IM regions. The density of S-CD3+ cells was significantly higher in mLNs than in PTs for both CT and IM regions (P < 0:0001), whereas that of S-CD8+ cells was so only in the IM (P < 0:0001). The densities of stromal T cells and cytotoxic T cells were also significantly correlated between PTs and mLNs (P < 0:0001) (Figure 2; Supplementary Table 1).

Different
Immune-Mediated Response in mLN and PT after Neoadjuvant Immunotherapy. In a patient with stage IIIa (N2) SCC who received three cycles of neoadjuvant pembrolizumab+chemotherapy (Supplementary Material), the percentage of immune-related residual viable tumor was 60% in PT and 0% in mLNs following complete resection. Both PT and mLNs showed immune-mediated responses such as proliferative fibrosis, neovascularization, and necrosis. However, foamy macrophages and cholesterol clefts were found exclusively in mLN. Interestingly, the densities of S-CD3+ in CT and IM regions as well as S-CD8+ in CT region in PT were significantly lower than in mLNs (P = 0:0016). The density of S-PD-L1+CD3+ was only significantly higher in mLN than in PT at CT (P = 0:047). No difference was found in the densities of S-CD8+ and S-PD-L1+CD3+ between PT in IM region and mLNs, which may be due to higher densities of these cells at IM than at CT   Table 3). Data extracted from five neoadjuvant immunotherapy trials also showed that there were different pathological responses between mLNs and PTs. Complete nodal clearance (ypN0) was more likely to occur than pathological complete response in the PT (ypT0) in NSCLC patients following neoadjuvant immunotherapy (odds ratio = 3:56; 95% confidence interval 2.14-5.92; P < 0:001; Supplementary

Discussion
We conducted a comparative study of the in situ immune patterns of PTs and mLNs of NSCLC patients regarding the spatial distributions and densities of CD3+ and CD8+ TILs and the PD-L1 expression statuses of tumor cells and stromal CD3+ TILs. Results showed that the densities of T-CD3+ and T-CD8+ cells were not significantly different yet significantly correlated between PTs and mLNs in the tumor compartment, i.e., the in situ immune patterns of T-CD3+ and T-CD8+ were homogenous. Although the densities of S-CD3+ and S-CD8+ were significantly correlated,   7 Journal of Immunology Research their in situ immune patterns were heterogeneous, with a higher density of the former at CT and IM and a higher density of the latter at IM in mLNs.
Interestingly, Remark et al. reported similar results for PTs and lung metastases in CRC and renal cell carcinoma (RCC) patients [33]. In their work, the densities of CD8+, DC-LAMP+, and NKp46+ TILs (markers of cytotoxic T cells, mature dendritic cells, and natural killer cells, respectively) were positively correlated between primary CRC and RCC tumors and corresponding lung metastases (r = 0:656 to 0.693 for CRC and 0.547 to 0.817 for RCC). However, the densities of CD8+ T cells of CRC-PT and DC-LAMP+ TILs of RCC-PTs were significantly higher than in lung metastases. It is possible that the in situ immune pattern reproduced from PTs to metastases occurs not only in CRC and RCC but also in NSCLC, and the reproducibility was shown in both CT and IM regions in our study. This supports the theory that there is imprinting of the TIME by tumor cells as the immune cells are "educated" by the immune contexture of PT and recalled at metastatic sites [33].
Patients with a preexisting T cell-infiltrated tumor microenvironment are more likely to respond to immunotherapy, as the checkpoint inhibitors can enhance the preexisting immune response and may induce new T cell-mediatedimmune responses [7]. Melanoma with a higher density of CD8+ cells in the IM region had a better response to the immunotherapy and exhibited a parallel increase in CD8+ cells in both the IM and CT regions [34]. Wu et al. reported that patients with higher frequencies and densities of stromal PD-L1-positive regulatory T cells (CD25+ CD4+) and PD-1positive CD8+ T cells have a better response to immunotherapy [25]. In this study, we investigated the PD-L1 expression status of stromal tumor-infiltrating T cells in terms of density and location in PTs and mLNs. The densities of S-PD-L1+CD3+ at CT were significantly correlated between PTs and mLNs. However, only a marginally significant correlation was found at IM. The densities and frequencies of S-PD-L1+CD3+ were higher in mLNs than in PTs in both regions. These results suggest that PD-L1 expression of stromal tumor-infiltrating T cells differs between PTs and mLNs,  10 Journal of Immunology Research and the ongoing immune response is stronger in mLNs than in PTs in NSCLC patients. The preclinical study had proved that tumor-draining, but not nondraining, lymph nodes served to accumulate T cells required for checkpoint blockade therapy to the PT [35]. To assess whether the finding in this study affects the response to neoadjuvant immunotherapy, a stage IIIa SCC that underwent neoadjuvant chemoimmunotherapy was investigated. Interestingly, the percentage of immunerelated residual viable tumor of PT and mLNs was 60% and 0%. The discrepant immune-related pathologic response between PT and mLNs may result from a more intense immune response in mLNs than in PT at CT region as the densities of S-CD3+, S-CD8+, and S-PD-L1+CD3+ were higher in mLNs. Besides, the densities of S-CD8+ and S-PD-L1+CD3+ in IM region of PT were not different from mLNs. These results suggest that the immune response of IM in PT was similar to mLNs and stronger than of CT in PT, and IM region may serve as a frontline during the antitumor response, which results in immune-mediated features like the regression bed [28]. According to the study of Ling et al., the PT and mLN show various immune phenotypes following neoadjuvant immune checkpoint inhibitor monotherapy [36]. Considering that the pathological response of NSCLC after neoadjuvant immunochemotherapy is generally greater than that of anti-PD-1 monotherapy, the change of immune pattern by different neoadjuvant regimens remains to be investigated. Several studies have compared the PD-L1 expression status of tumor cells between PTs and mLNs in NSCLC patients [27,37,38]. Uruga et al. reported that the discrepancy rate between PTs and mLNs was 9.4% to 15% [38]. In Kim et al., the concordance rate between PTs and metastatic sites (83.2% were regional lymph nodes) was 80.1% (κ = 0:492) in ADC patients [27]. Sakakibara et al. suggested that the expression levels of PD-L1 in tumor cells were significantly correlated between PTs and resected mLNs (r = 0:49, P < 0:001) [37]. In our study, the concordance rate of PD-L1 positivity between PTs and mLNs was 66% (κ = 0:302), and the TPS (%) between PTs and mLNs were significantly correlated.
Conversely, few studies have compared the CPS between PTs and mLNs. CPS which integrates all PD-L1-expressing cells (tumor cells, lymphocytes, and macrophages) is a prognostic indicator in patients treated with pembrolizumab [26,39]. In this study, the concordance rate of CPS status was 60% (κ = 0:116) and was not correlated between PTs and mLNs. More heterogeneity in CPS than the TPS between PTs and mLNs may be explained by the composition of cells other than tumor cells differing dramatically between PTs and mLNs. Given that PD-L1 expression in stromal tumorinfiltrating T cells was higher in mLNs than in PTs, we postulated that the PD-L1 expression status of lymphocytes and macrophages would be heterogeneous, resulting in the discrepancy of CPS. Nodal status following induction therapy in NSCLCs affects the final pathological stage and thus determines the potential adjuvant therapeutic strategy after operation. As indicated by a recent published research, nodal disease status following neoadjuvant chemotherapy is a key determinant of survival among patients with a major pathological response within the primary tumor [40]. It is plausible that the findings of the current study may have an impact on patients who undergo neoadjuvant immunotherapy.
Interestingly, the pathological response following neoadjuvant immunotherapy had been validated in several phase II trials, with major pathological response rates ranging from 18% to 83% [28][29][30][31][32]. The extracted data from these trials indicated that for patients who achieved a pathological complete response in their PTs, there was a high tendency that the mLNs may experience downstaging to ypN0 following neoadjuvant immunotherapy. This may, to some extent, support the findings of the current study that there could be a more extensive response in the lymph nodes following immunotherapy.
The current study had several limitations. First, only patients with stage III (N2) disease without an EGFR mutation or EML4-ALK translocation were included, as such patients would likely derive the greatest benefit from neoadjuvant immunotherapy. Therefore, the results may not be generalizable to other populations of NSCLC patients. Second, potential bias due to the small sample size did exist in this study, and we could not assess whether the diverse in situ immune patterns between PTs and mLNs had a prognostic impact on patients following surgery. Third, though the results from the pooled analysis of published trials were used to indicate a potentially higher response rate of mLN following induction immunotherapy compared with PT, only one case was depicted in this study to demonstrate the associated microenvironment. Whether the different immune-mediated responses in PT and mLN observed in this patient were related to the heterogeneity of the in situ immune patterns still needed further investigation for lacking the evaluation of preoperative samples of PT and mLNs in terms of baseline PD-L1 expression and TIL status. Last but not the least, the TILs assessed were limited to only two markers (CD3 and CD8). To evaluate in situ immune patterns more comprehensively, other markers such as CD4 (helper T cell marker), CD45RO (memory T cell), CD68 (macrophage), and FOXP3 (regulatory T cell) should be investigated.

Conclusion
Different in situ immune patterns of S-CD3+ and S-CD8+ as well as PD-L1 expression status of stromal T cells may result in different immune-related pathologic response between PTs and mLNs in NSCLC patients. Further studies are needed to clarify whether these phenomena impact the treatment and prognosis of NSCLC, particularly in the setting of neoadjuvant immunotherapy.

Data Availability
The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

Ethical Approval
This study was conducted in accordance with the amended Declaration of Helsinki (as revised in 2013). The institutional review board approved the study protocol (SYSUCC B2019-116-01).